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Visual programming language

Visual programming language
In computing, a visual programming language (VPL) is any programming language that lets users create programs by manipulating program elements graphically rather than by specifying them textually. A VPL allows programming with visual expressions, spatial arrangements of text and graphic symbols, used either as elements of syntax or secondary notation. For example, many VPLs (known as dataflow or diagrammatic programming)[1] are based on the idea of "boxes and arrows", where boxes or other screen objects are treated as entities, connected by arrows, lines or arcs which represent relations. Definition[edit] VPLs may be further classified, according to the type and extent of visual expression used, into icon-based languages, form-based languages, and diagram languages. Visual programming environments provide graphical or iconic elements which can be manipulated by users in an interactive way according to some specific spatial grammar for program construction. Visual languages[edit] Related:  visual programmingProgramming

Processing.org Directed acyclic graph An example of a directed acyclic graph In mathematics and computer science, a directed acyclic graph (DAG DAGs may be used to model many different kinds of information. A collection of tasks that must be ordered into a sequence, subject to constraints that certain tasks must be performed earlier than others, may be represented as a DAG with a vertex for each task and an edge for each constraint; algorithms for topological ordering may be used to generate a valid sequence. Partial orders and topological ordering[edit] A Hasse diagram representing the partial order ⊆ among the subsets of a three-element set. Each directed acyclic graph gives rise to a partial order ≤ on its vertices, where u ≤ v exactly when there exists a directed path from u to v in the DAG. Every directed acyclic graph has a topological ordering, an ordering of the vertices such that the starting endpoint of every edge occurs earlier in the ordering than the ending endpoint of the edge. Data processing networks[edit]

Prolog Prolog is a general purpose logic programming language associated with artificial intelligence and computational linguistics.[1][2][3] Prolog has its roots in first-order logic, a formal logic, and unlike many other programming languages, Prolog is declarative: the program logic is expressed in terms of relations, represented as facts and rules. A computation is initiated by running a query over these relations.[4] The language was first conceived by a group around Alain Colmerauer in Marseille, France, in the early 1970s and the first Prolog system was developed in 1972 by Colmerauer with Philippe Roussel.[5][6] Prolog was one of the first logic programming languages,[7] and remains the most popular among such languages today, with many free and commercial implementations available. Prolog is well-suited for specific tasks that benefit from rule-based logical queries such as databases searching, voice control systems, and template filling. §Syntax and semantics[edit] §Data types[edit] ? ? ? ?

App Inventor Get Started Follow these simple directions to build your first app! Tutorials Step-by-step guides show you how to create even more apps. Teach Find out about curriculum and resources for teachers. Forums Join community forums to get answers to your questions. Machine learning Machine learning is a subfield of computer science[1] that evolved from the study of pattern recognition and computational learning theory in artificial intelligence.[1] Machine learning explores the construction and study of algorithms that can learn from and make predictions on data.[2] Such algorithms operate by building a model from example inputs in order to make data-driven predictions or decisions,[3]:2 rather than following strictly static program instructions. Machine learning is closely related to and often overlaps with computational statistics; a discipline that also specializes in prediction-making. It has strong ties to mathematical optimization, which deliver methods, theory and application domains to the field. Machine learning is employed in a range of computing tasks where designing and programming explicit, rule-based algorithms is infeasible. Overview[edit] Tom M. Types of problems and tasks[edit] History and relationships to other fields[edit] Theory[edit]

Setting Up App Inventor 2 You can set up App Inventor and start building apps in minutes. The Designer and Blocks Editor run completely in the browser (aka the cloud). To see your app on a device while you build it (also called "Live Testing"), you'll need to follow the steps below. You have three options for setting up live testing while you build apps If you are using an Android device and you have a wireless internet connection, you can start building apps without downloading any software to your computer. If you do not have an Android device, you'll need to install software on your computer so that you can use the on-screen Android emulator. If you do not have a wireless internet connection, you'll need to install software on your computer so that you can connect to your Android device over USB. Option One - RECOMMENDEDBuild apps with an Android device and WiFi Connection (preferred): Instructions If you have a computer, an Android device, and a WiFi connection, this is the easiest way to test your apps.

pyc/weblog» Blog Archive » node graph Having looked at other alternatives (i.e. html5 canvas, ajax, js with framwork), Flash wtih as3 is chosen for the UI for I have some experience with it a while back, also it has the ability to communicate with javascript and be embeded on web as well as standalone exe. From what I know there is no readily available framework/library. After seeing such progressive UI (as some would call) imbued in many of the current 3d applications (i.e. grasshopper, houdini, maya and max), I have decided to start this personal project to explore the inner workings of node graphs in general by making one as a script editor for maya (through as3 native socket or python socket as cgi) and possibly sketchup (through ruby webdialog to javascript to as3) Node graph is nothing new as a data visualisation tool or program extension.

OPS5 The OPS (said to be short for "Official Production System") family was developed in the late 1970s by Charles Forgy while at Carnegie Mellon University. Allen Newell's research group in artificial intelligence had been working on production systems for some time, but Forgy's implementation, based on his Rete algorithm, was especially efficient, sufficiently so that it was possible to scale up to larger problems involving hundreds or thousands of rules. OPS5 uses a forward chaining inference engine; programs execute by scanning "working memory elements" (which are vaguely object-like, with classes and attributes) looking for matches with the rules in "production memory". In this sense, OPS5 is an execution engine for a Petri net extended with inhibitor arcs. The OPS5 forward chaining process makes it extremely parallelizeable during the matching phase, and several automatic parallelizing compilers were created. OPS4 was an early version, while OPS83 came later. References[edit]

Модульные технологии: от Lego до Google Blockly Технологии Людям всегда нравилось изобретать что-то новое. Однако для плодотворного творчества требуется не только личная одарённость, но и среда, позволяющая реализовать новые идеи. Классический пример такой среды — детские кубики, из которых можно построить дом, замок — или сложить разные слова. Не менее классическими можно назвать и знаменитые «кирпичики» Lego. Положенный в основу таких наборов принцип отлично работает и на более сложных уровнях, причём как в материальном мире, так и в мире алгоритмов. 1. Хотя сама идея изготовления одинаковых блоков, которые можно соединять друг с другом, восходит к глубокой древности, самая удачная её реализация принадлежит датской компании Lego, которая в 1947 году приступила к выпуску пластмассовых игрушек, а в 1949-м — знаменитых элементов LEGO. Отличная иллюстрация самой сути модульного подхода: из элементарных «кирпичиков» можно собрать как самые простые модели, так и невероятно сложные конструкции. 2. 3. 4. littleBits (2011) 5. 6. 7. 8. 9. 10.

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